[qnleigh]

I suspect there's a bit of a chance to learn from history here. It was predicted that radiologists would get put out of the job by AI tools. But this didn't happen, largely because trust and liability matter just as much as the service itself.

This isn't a counterargument to the idea that AI is going to kill a lot of app subscriptions, but it tells us about what kinds of apps will get killed, and what apps will have staying power. Ironically, the flood of cheap, low quality AI generated apps might make it harder for cheap apps to overtake bigger players, because overall trust in the ecosystem will go down.

[ghywertelling]

The areas where errors are tolerated with human / "classical algo" fallback is the best field to disrupt with AI. Call center jobs. Recommendations. Search, Curation. Wherever the current process is already stochastic and has a human or rule-based correction loop, AI just needs to be cheaper and roughly as accurate to win.

[CamperBob2]

It's early days yet. You'd have to be crazy to go into radiology, if you were just starting out as a freshly-minted MD. And yes, this is going to be a problem, possibly a big one.

See also: air traffic control.

[Kbelicius]

> You'd have to be crazy to go into radiology

People were saying that a decade ago, if not more, with machine learning outperforming radiologists. Today we don't have enough radiologists. What has changed since those days that one can again say that so confidently?

[J_Shelby_J]

“Claude write me an app to do air traffic control. Make sure planes don’t crash. Here is a hundred years of rules and their context.”